My Future of Work class at NYU kicks off with the ritual rearrangement of the room set-up. Students know to break up the rows of chairs to create pods and place themselves around the room. The instructor’s spot also needs to shift. The pods take up most of the class space and leave just enough room for the instructor to maneuver in between chairs joining different pods as students work on assignments and projects.
By the start of the second session, the room rearrangement ritual becomes the way we do things around here. As students trickle into the classroom, furniture gets moved, teams form themselves spontaneously, and conversations begin to freely flow as new bonds form and strengthen.
As the context of work changes and technology gets smarter, faster, cheaper, and even more human, the right question for Learning professionals to ask is about the impact these changes have on learning. What would learning look like in 2030 if it were to remain the principal pathway for the next generation’s relevance, competitiveness, and ultimate success?
Double-Edged Sword
Business media today are sounding the alarm about the growing gap between automation of work and workers’ readiness to adopt these new intelligent technologies. The hardest challenge for many is to change from execution to innovation and from compliance to problem solving. In other words, both sides of the brain need to be fired up to deliver. The majority of current solutions understandably are focused on reskilling, upskilling, and training in these new technologies. The language of learning today is sounding more like that of a revolution than an evolution. Take the January 2019 World Economic Forum report produced in collaboration with Boston Consulting Group (BCG) and Burning Glass Technologies entitled: Towards a Reskilling Revolution: Industry-Led Action for the Future of Work. The report outlines the root causes of the reskilling challenges and the steps needed to address them, i.e., recommendations for preparing the workforce of the future.
It does feel intuitive to turn to technology for help. There is no question that “hard” skills matter. In the beginning, technology seemed to provide the ubiquitous, personalized, and scalable solution for the Google-bred generation of learners. But we have discovered the hard way that technology itself is Janus-like when it comes to learning. It is both the cause of the problems we have, as well as the solution. Technology personalizes and serves up the needed content, but it also socially isolates and distracts.
It’s Not So Simple
According to a recent survey by the Center for Digital Education—a research and advisory institute specializing in technology trends, policy, and funding in education—tech-enabled learning has emerged as the educational priority for K-12 and for the higher-education institutions around the country. Tech ed also became a major priority of the Bill & Melinda Gates Foundation and the Chan Zuckerberg Initiative (the commitment), the Facebook founder’s philanthropy investing millions of dollars annually into Group (BCG) and Burning Glass Technologies entitled: Towards a Reskilling Revolution: Industry-Led Action for the Future of Work. The report outlines the root causes of the reskilling challenges and the steps needed to address them, i.e., recommendations for preparing the workforce of the future.
It does feel intuitive to turn to technology for help. There is no question that “hard” skills matter. In the beginning, technology seemed to provide the ubiquitous, personalized, and scalable solution for the Google-bred generation of learners. But we have discovered the hard way that technology itself is Janus-like when it comes to learning. It is both the cause of the problems we have, as well as the solution. Technology personalizes and serves up the needed content, but it also socially isolates and distracts.
And yet, despite significant investments, the hype around technology being the panacea for educational challenges seems to be blowing up. Here is why it is not so simple: Just like anything in fast-moving tech, we still do not know the full impact of new technologies on learning motivation; work ethic; and the ability to focus, problem solve, and collaborate. The science is lagging and still has to demonstrate the full impact of emerging technologies such as artificial intelligence (AI), virtual reality (VR), and other types of automation on humans’ ability to learn.
As much as Learning professionals need to embrace and celebrate the benefits technology brings to education, they need to confront the dystopian side of educational technology and openly challenge the “new shiny objects” emerging in the market every day.
We need to watch closely and learn as the first tech-raised generation is entering the workforce. Are we sacrificing learning as a shared social interaction for the interaction with the screen? If you take away the ability for people to set and achieve goals together and overcome challenges on the team…you may lose one of the important outcomes of in-person learning—collaboration. Could that be why the innovation-focused tech companies are calling back their remote employees to work together on agile teams?
Educational software is not exempt from bias either. Baked into the algorithms are their creators’ assumptions. Algorithms may sort out students unfairly. They may typecast, put up roadblocks, and make assumptions about how students should be thinking. It has been pointed out that educators themselves show bias. Yet teachers can remedy their bias and demonstrate empathy and understanding, while software cannot. At least, not yet.
The Evolution
Without question, technology will play an oversized role in learning in 2030. But so will human teachers, peers, families, and communities at large. Together, we will need to evolve from us learning about technology to technology learning about us.
Today, we have already started on that journey. As technology serves up content, we amplify the human connections. Here are just some technology functions that already are helping the social aspects of learning to succeed:
- Technology serves up feedback, the key ingredient in successful learning.
- Collaborative platforms help teams connect, record, measure, and remind about the work being done.
- Technology accelerates testing and runs multiple experiments to help deliver results.
- Technology facilitates creation of an ecosystem where learning can thrive.
Back in my NYU classroom, I engage students in collaborative learning from the start on the journey to the Future of Work. Technology at their side, students work in pods, think together through problems, and design the future for themselves. When asked if they want to do it online, universally, students choose the face-to-face interaction. To me, learning 2030 will be about humans becoming more human, while technology will assist. In the words of London School of Economics Professor Minouche Shafik: “In the past, jobs were about muscles; now they’re about brains; but in the future, they’ll be about the heart…”
Anna A. Tavis, Ph.D., is the academic director of the Human Capital Management Programs at NYU. With Rita Bailey, she is co-facilitating Training magazine’s Learning Leaders Summit Feb. 22-23 at Training 2020 in Orlando, along with leaders from Visa, AdventHealth, Amazon, EY, Mastercard, PwC, IBM, and others. Find out more and join us: www.trainingconference.com.